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Analysisstrong confidence 4 of 5: Replicated in peer-reviewed work by more than one group.Q-histone-marks

Every gene in the H2B ubiquitination axis, ranked against the whole genome for KMT2A selectivity — and the writers are not selective

also called H2Bub machinery DepMap lookup · RNF20 selectivity null

We looked up every enzyme that writes, carries or erases the H2B ubiquitin tag in a ready-made scan of 17,728 genes that ranks how much more KMT2A-rearranged leukaemia cells need a gene than other leukaemia cells do. The enzymes that write the tag came out flat or backwards; only the erasing side produced anything.

The same thing, for a scientist

🟠 **ARM-COMPOSITION CAVEAT ADDED 2026-09-24 (cycle 140).** This entry's computation rests on `analyses/depmap-kmt2a-selective-scan-full`, and that scan **fixes both comparison arms from the first gene that returns screen data** (`run.py:170`, `if rear is None:`; line 174 prints *"Groups fixed from first gene with data"*). Because DepMap screens each gene in a gene-specific set of lines, **5 of 16 eligible KMT2A-rearranged lines are excluded from every gene comparison, including genes where they were screened** - 16 resolve under the scan's own query, 11 were used. **This does not show any conclusion here is wrong.** Dropping 5 of 16 costs power, and it biases a ranking only if the dropped lines differ systematically from the kept ones, **which nobody has tested.** The named one-line fix is to derive the arms from each gene's own screen list. Until the scan is re-run, selectivity ranks taken from it carry an unquantified arm-composition caveat. Found by `analyses/depmap-scan-line-identities` on 2026-09-21 and unreported until now; see `ana-the-depmap-selectivity-scan-fixes-its-arms-from-the-first-gene-and-drops-five-of-sixteen-lines-from-every-comparison`. --- The premise of this beat is that H2B ubiquitination is upstream of the most-cited mechanistic step in KMT2A-rearranged leukaemia and absent from the graph. The premise is correct. The natural corollary — that the machinery is therefore a target — is what this analysis tests, using the project's existing full genome-wide scan (`analyses/depmap-kmt2a-selective-scan-full`, 17,728 protein-coding genes, 11 Cellosaurus-annotated KMT2A-rearranged versus 43 other leukaemia lines) with no new computation, only lookups of `all_results`. **The writers fail.** RNF20 ranks 16,229 of 17,728 — its difference is *positive*, meaning marginally less required in the rearranged lines — while being broadly essential (-0.734). RNF40 (rank 9,953), WAC (7,779), UBE2A (6,504), UBE2B (10,016), UBE2E1 (17,038) and MSL2 (7,112) are all flat. **The erasers do better.** USP22 ranks 226 and ATXN7L3 ranks 290, both in the top 1.6% of the genome, but ENY2 — ATXN7L3's own module partner — ranks 11,080, which is an internal inconsistency that argues for caution. For scale, MEN1 ranks 1 and DOT1L ranks 184 in the same scan.

Go deeper
The table

Difference = mean Chronos gene effect in 11 KMT2A-rearranged leukaemia lines minus mean in 43 other leukaemia lines. More negative = more selectively required in KMT2A-rearranged lines. Pan = mean across all 1,208 lines.

GeneRoleKMT2A-rother leukdifferencerank / 17,728pan
MEN1benchmark-1.263-0.397-0.8661-0.363
KMT2Abenchmark-0.811-0.270-0.54111-0.206
DOT1Lbenchmark-0.604-0.373-0.231184-0.148
USP22H2Bub eraser (SAGA DUB)-0.130+0.082-0.211226+0.089
ATXN7L3DUB adaptor-0.446-0.258-0.188290-0.336
LEO1PAF1C-0.420-0.252-0.168367-0.213
RTF1PAF1C, required for H2Bub-0.703-0.620-0.0831,645-0.666
MSL1H2BK34ub complex-0.449-0.376-0.0732,078-0.365
USP51H2Bub eraser-0.006+0.050-0.0572,992-0.004
PAF1PAF1C-0.818-0.780-0.0384,529-0.832
UBE2Acandidate E2-0.173-0.153-0.0206,504-0.162
SKIC8PAF1C-0.831-0.815-0.0167,012-0.746
MSL2H2BK34 E3-0.111-0.096-0.0157,112-0.083
WACH2Bub adaptor-0.393-0.383-0.0117,779-0.389
KAT8MOF, same complex as MSL2-1.489-1.493+0.0049,683-1.452
RNF40H2Bub E3-0.520-0.527+0.0069,953-0.490
UBE2Bcandidate E2+0.080+0.073+0.00710,016+0.049
ENY2DUB adaptor-0.335-0.350+0.01511,080-0.313
CDC73PAF1C-1.177-1.196+0.02011,645-1.122
USP27XH2Bub eraser+0.101+0.073+0.02812,583+0.075
RNF20H2Bub E3-0.658-0.735+0.07616,229-0.734
UBE2E1candidate E2 (UbcH6)+0.098-0.010+0.10817,038-0.007
CTR9PAF1C-0.854-0.999+0.14617,413-0.873
What this does and does not overturn

It does not overturn Wang et al. 2013. That paper showed Rnf20 suppression inhibits proliferation of MLL-rearranged leukaemia models in vitro and in vivo and lowers Dot1l-dependent H3K79me at Hoxa9 and Meis1. This analysis agrees that RNF20 is required — the KMT2A-rearranged mean gene effect is -0.658, a real dependency. What it adds is the comparator that paper did not run: other leukaemia lines need RNF20 just as much (-0.735). Necessity, yes. Selectivity, no.

It does not prove there is no window. Three specific reasons to hold the null loosely:

  1. Eleven lines, AML-weighted, none infant-derived. The two KMT2A-specific H2Bub papers are an AML-model study and an infant B-ALL xenograft study. The DepMap panel does not represent the second.
  2. CRISPR knockout compresses differences for essential genes. When both arms die, the difference between them shrinks. RNF20's pan-essentiality of -0.734 is exactly the regime where this matters.
  3. Redundancy is invisible to single-gene knockout. Three candidate E2s all score flat; three H2Bub DUBs all score flat or modest. That is the signature of redundancy, and DepMap cannot see a requirement shared across paralogues.

What it does establish is that the burden of proof has moved. Anyone proposing RNF20/RNF40/WAC as a KMT2A-rearranged target now has to explain a genome-wide rank of 16,229 — and the honest place to look for the explanation is an infant B-ALL model, because that is the context DepMap does not cover.

Facts and figures
scriptanalyses/depmap-kmt2a-selective-scan-full/run.py
statusrun
result summaryThe H2Bub writers show no KMT2A selectivity (RNF20 rank 16229, RNF40 9953, WAC 7779, all three candidate E2s flat, MSL2 7112). The erasers do: USP22 rank 226 and ATXN7L3 rank 290, though ENY2 in the same module ranks 11080. Benchmarks MEN1 rank 1, KMT2A 11, DOT1L 184.
method noteLookup only; no recomputation. Values taken from the all_results array of the existing scan.
n genes looked up23
arm composition caveat cycle 140source scan fixes both arms from the first gene with data (run.py:170); 5 of 16 eligible KMT2A-rearranged lines are excluded from every comparison. Effect on this entry's conclusion untested.
inputs
[
  "analyses/depmap-kmt2a-selective-scan-full/results.json (all_results, 17728 genes)"
]
How this could bite us back
  • A null from an underpowered panel is not the same as an absence, and this project has previously over-read DepMap in both directions. The correct use of this table is to raise the burden of proof on the writers, not to close the question.
  • Conversely, the two eraser hits (USP22, ATXN7L3) come from the same underpowered panel and deserve exactly the same scepticism they would receive if they had pointed the other way.
Still open
  1. Does RNF20 show selectivity in infant B-ALL models specifically? That is the one context where the positive literature lives and the one context DepMap does not cover.
  2. Would a titratable degron rather than a knockout reveal a window for RNF20 that CRISPR compresses away? The pan-essentiality of -0.734 is exactly where this concern bites.
  3. Is the USP22/ATXN7L3 pair a real signal, given ENY2's null? A single knockout experiment in matched lines settles it.
  4. Should the scan be re-run restricted to B-lineage lines? The panel is AML-weighted and this project's disease is not.
Every source behind this entry (1)
  1. E1strong confidence 4 of 5: Replicated in peer-reviewed work by more than one group.dataset

    Lookups of the project's existing genome-wide DepMap KMT2A-selectivity scan give, for the H2B ubiquitination axis: RNF20 difference +0.076 (rank 16,229/17,728, pan -0.734); RNF40 +0.006 (9,953, -0.490); WAC -0.011 (7,779, -0.389); UBE2A -0.020 (6,504, -0.162); UBE2B +0.007 (10,016, +0.049); UBE2E1 +0.108 (17,038, -0.007); MSL2 -0.015 (7,112, -0.083); MSL1 -0.073 (2,078, -0.365); KAT8 +0.004 (9,683, -1.452); USP22 -0.211 (226, +0.089); ATXN7L3 -0.188 (290, -0.336); ENY2 +0.015 (11,080, -0.313); USP51 -0.057 (2,992, -0.004); USP27X +0.028 (12,583, +0.075); RTF1 -0.083 (1,645, -0.666); LEO1 -0.168 (367, -0.213); PAF1 -0.038 (4,529, -0.832); CTR9 +0.146 (17,413, -0.873); CDC73 +0.020 (11,645, -1.122); SKIC8 -0.016 (7,012, -0.746); with MEN1 -0.866 (rank 1), KMT2A -0.541 (rank 11) and DOT1L -0.231 (rank 184) as benchmarks.

    What this evidence cannot show

    No new computation was performed for this entry; every value is a lookup of the existing scan's per-gene results, so this analysis inherits every caveat of that scan: 11 KMT2A-rearranged lines, none infant-derived and the group AML-weighted; possible incompleteness of Cellosaurus fusion annotation, which biases toward the null; differences not permutation-tested per gene; and no correction for the fact that CRISPR knockout compresses apparent selectivity for pan-essential genes. DepMap release version is not reported by the API.

    Evidence that argues against this (1)
    • Two primary papers report that this machinery is required in MLL-rearranged leukaemia - Wang et al. 2013 (RNF20, shRNA, multiple models, in vivo) and Garrido Castro et al. 2018 (RNF20/RNF40/WAC axis in infant/paediatric MLL-rearranged ALL xenografts, with WAC knockdown phenocopying H2Bub loss). Neither is contradicted by a null on selectivity, and the second works in the B-ALL context that this DepMap panel does not represent. Garrido Castro P et al. 2018
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